Project Summary Cancer is a leading cause of death in the US. Research has demonstrated that poor dietary habits are a major preventable cause of cancer. Americans are burdened by suboptimal dietary intake. Improving diet is clearly a priority for reducing burdens of cancer in the US. Unfortunately, the optimal strategies to improve diet and reduce cancer are not clear. While various individual-level behavioral change approaches can be effective for some people, overall benefits and long-term adherence may be modest and overall benefits poorly sustained. In contrast, population-based strategies can be more powerful and sustainable, and achieve broader impact. We have systematically reviewed and synthesized the evidence-base for effects of various population interventions on dietary intake and identified several strategies with the strongest evidence-base. However, the effectiveness of these strategies on reducing cancer burden has not been quantified. In addition, the cost for implementing these strategies is largely unknown; and the cost-effectiveness of implementing these interventions has not been established. To address these major gaps in knowledge, we have selected population-based strategies to improve specific dietary targets that have the strongest evidence for effects on cancer incidence, in the realms of (1) media/education, (2) food labeling/information, (3) taxation/subsidies, and (4) regulations/quality standards. We will develop two population-based models: (a) a Comparative Risk Assessment (CRA) model; and (b) a health policy state transition Markov model with Monte Carlo simulation, the Diet Cancer Outcome Model (DiCOM), to quantify and compare the effectiveness of these interventions by estimating the numbers of cancer incidence and deaths reduced, disability-adjusted life years (DALYs) averted, and quality-adjusted life years (QALYs) gained in the US population, with projections over 5, 10, 15, and 20 years. Second, we will develop costing protocols to estimate the cost of implementing specific population-based dietary interventions from a societal perspective, and subsequently assess the cost- effectiveness of the interventions by calculating the incremental cost-effectiveness ratio (ICER) per QALY gained. We will further evaluate the impact of implementing population-based dietary interventions to reduce cancer disparities in disadvantaged groups as exploratory analyses. The robustness of estimates will be assessed with extensive sensitivity analyses to varying assumptions on model parameters and assumptions. This study will provide, for the first time, the effectiveness estimates of well-defined population strategies to improve targeted dietary factors and reduce cancer burden in the US, which are crucial to informing dietary healthy policy making and evidence-based cancer prevention efforts.